说话人识别源代码（DTW）

clc clear %----------MFCC及其差分为特征参数的参考模板------------------------ disp('正在计算参考模板的参数....') for i = 1:5 fname = sprintf('d:\\matlab6p5\\work\\single\\number\\A\\%d.wav',i); %fname = sprintf('d:\\matlab6p5\\work\\sound\\unsime\\11\\%d.wav',i); x = wavread(fname); %小波消噪 [C,L] = wavedec(x,3,'db4'); [thr,sorh,keepapp] = ddencmp('den','wv',x); de_noise = wdencmp('gbl',C,L,'db4',3,thr,sorh,keepapp); x = de_noise; %x = wden(x,'heursure','s','one',1,'sym8');%进行消噪处理 m = mfcc(x);%提取mel倒谱参数 %m = lpcmc(x); %t = Pit(x); %n = lpcc(x); %w = [m n]; %z = [m t]; ref1(i).mfcc = m;%存储MFCC参数 end %----------MFCC及其差分为特征参数的参考模板------------------------ disp('正在计算参考模板的参数....') for i = 1:5 fname = sprintf('d:\\matlab6p5\\work\\single\\number\\A\\%d.wav',i); %fname = sprintf('d:\\matlab6p5\\work\\sound\\unsime\\11\\%d.wav',i); x = wavread(fname); %小波消噪 [C,L] = wavedec(x,3,'db4'); [thr,sorh,keepapp] = ddencmp('den','wv',x); de_noise = wdencmp('gbl',C,L,'db4',3,thr,sorh,keepapp); x = de_noise; %x = wden(x,'heursure','s','one',1,'sym8');%进行消噪处理 %m = mfcc(x);%提取mel倒谱参数 %m = lpcmc(x); %t = Pit(x); n = lpcc(x); %w = [m n]; %z = [m t]; ref2(i).lpcc = n;%存储MFCC参数 end %----------------MFCC及其差分为特征参数的测试模板--------------------------- disp('正在计算测试模板的参数....') for i = 1:1 fname = sprintf('d:\\matlab6p5\\work\\single\\number\\E\\%d.wav',i); %fname = sprintf('d:\\matlab6p5\\work\\sound\\unsime\\12\\%d.wav',i); x = wavread(fname); %小波消噪 [C,L] = wavedec(x,3,'db4'); [thr,sorh,keepapp] = ddencmp('den','wv',x); de_noise = wdencmp('gbl',C,L,'db4',3,thr,sorh,keepapp); x = de_noise; %x = wden(x,'heursure','s','one',1,'sym8');%进行消噪处理 m = mfcc(x);%提取mel倒谱参数 %m =lpcmc(x); %t = Pit(x); %n = lpcc(x); %w = [m n]; %z = [m,t]; test1(i).mfcc = m;%存储MFCC参数 end %----------------LPCC及其差分为特征参数的测试模板--------------------------- disp('正在计算测试模板的参数....') for i = 1:1 fname = sprintf('d:\\matlab6p5\\work\\single\\number\\E\\%d.wav',i); %fname = sprintf('d:\\matlab6p5\\work\\sound\\unsime\\12\\%d.wav',i); x = wavread(fname); %小波消噪 [C,L] = wavedec(x,3,'db4'); [thr,sorh,keepapp] = ddencmp('den','wv',x); de_noise = wdencmp('gbl',C,L,'db4',3,thr,sorh,keepapp); x = de_noise; %x = wden(x,'heursure','s','one',1,'sym8');%进行消噪处理 %m = mfcc(x);%提取mel倒谱参数 %m =lpcmc(x); %t = Pit(x); n = lpcc(x); %w = [m n]; %z = [m,t]; test2(i).lpcc = n;%存储MFCC参数 end %---------------------MFCC参考模板和测试模板用DTW算法的模板匹配---------------------- disp('正在进行模板匹配....') dist = zeros(1,5); for i = 1:1 for j = 1:5 dist1(i,j) = dtw(test1(i).mfcc,ref1(j).mfcc); dist2(i,j) = dtw(test2(i).lpcc,ref2(j).lpcc); end end disp('正在计算匹配结果...'); for i = 1:1 [d1,j1] = min(dist1(i,:)); [d2,j2] = min(dist2(i,:)); if j1==j2 fprintf('测试模板%d的识别结果为：%d\n',i,j); else fprintf('测试模板%d的语音为非法人员',i); end end